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- paper-59 hasAuthorList authorList.
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- paper-59 title "Towards the Natural Ontology of Wikipedia".
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- paper-60 label "Do it yourself (DIY) Jeopardy QA System".
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- paper-60 abstract "This work demonstrates Treo, a framework which converges elements from Natural Language Processing, Semantic Web, Information Retrieval and Databases, to create a semantic search engine and question answering (QA) system for heterogeneous data. Jeopardy and Question Answering queries over open domain structured and unstructured data are used to demonstrate the approach. In this work, Treo is extended to cope with unstructured data in addition to structured data. The setup of the framework is done in 3 steps and can be adapted to other datasets by practitioners in a simple DIY process.".
- paper-60 hasAuthorList authorList.
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- paper-60 title "Do it yourself (DIY) Jeopardy QA System".
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- paper-61 type InProceedings.
- paper-61 label "A Machine Reader for the Semantic Web".
- paper-61 sameAs paper-61.
- paper-61 abstract "FRED is a machine reading tool for converting text into internally well-connected and quality linked-data-ready ontologies in web-service-acceptable time. It implements a novel approach for ontology design from natural language sentences, combining Discourse Representation Theory (DRT), linguistic frame semantics, and Ontology Design Patterns (ODP). The tool is based on Boxer which implements a DRT-compliant deep parser. The logical output of Boxer is enriched with semantic data from VerbNet (or FrameNet) frames and transformed into RDF/OWL by means of a mapping model and a set of heuristics following best practices of OWL ontologies and RDF data design. The current version of the tool includes Earmark-based markup, and enrichment with WSD and NER off-the-shelf components.".
- paper-61 hasAuthorList authorList.
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- paper-61 title "A Machine Reader for the Semantic Web".
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- paper-62 label "SEJP: Designing Interactive Scientometrics with Linked Data and Semantic Web Reasoning".
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- paper-62 abstract "In this demo paper we introduce a Linked Data-driven, Semantically-enabled Journal Portal (SEJP) that offers a variety of interactive scientometrics modules. SEJP allows editors, reviewers, authors, and readers to explore and analyze (meta)data published by a journal. Besides Linked Data created from the journal's internal data, SEJP also links out to other sources and includes them to develop more powerful modules. These modules range from simple descriptive statistics, over the spatial analysis of visitors and authors, to topics trending modules. While SEJP will be available for multiple journals, this paper shows its deployment to the Semantic Web journal by IOS Press. Due to its open & transparent review process, SWJ offers a wide variety of additional information, e.g., about reviewers, editors, paper decisions, and so forth.".
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- paper-62 title "SEJP: Designing Interactive Scientometrics with Linked Data and Semantic Web Reasoning".
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